Mapa de riesgo de invasión de macrófitos acuáticos exóticos de la Península Ibérica

Freshwater systems are particularly susceptible to non-native organisms, owing to their high sensitivity to the impacts that are caused by these organisms. Species distribution models, which are based on both environmental and socio-economic variables, facilitate the identification of the most vulnerable areas for the spread of non-native species. We used MaxEnt to predict the potential distribution of 20 non-native aquatic macrophytes in the Iberian Peninsula. Some selected variables, such as the temperature seasonality and the precipitation in the driest quarter, highlight the importance of the climate on their distribution. Notably, the human influence in the territory appears as a key variable in the distribution of studied species. The model discriminated between favorable and unfavorable areas with high accuracy. We used the model to build an invasion risk map of aquatic macrophytes for the Iberian Peninsula that included results from 20 individual models. It showed that the most vulnerable areas are located near to the sea, the major rivers basins, and the high population density areas. These facts suggest the importance of the human impact on the colonization and distribution of non-native aquatic macrophytes in the Iberian Peninsula, and more precisely agricultural development during the Green Revolution at the end of the 70’s. Our work also emphasizes the utility of species distribution models for the prevention and management of biological invasions.Los sistemas acuáticos son especialmente susceptibles a los organismos exóticos debido a su elevada fragilidad y a los impactos que provocan estas especies en este tipo de hábitats. Los modelos de distribución de especies, basados en variables ambientales y socioeconómicas, facilitan la identificación de las áreas más vulnerables ante la expansión de especies exóticas. Se utilizó MaxEnt para predecir la distribución potencial de 20 macrofitos exóticos en la Península Ibérica. Algunas de las variables estudiadas, como la estacionalidad de la temperatura y la precipitación del cuatrimestre más seco, ponen en evidencia la importancia de los factores climáticos en su distribución. Además, la influencia humana en el territorio se presenta como una variable clave en la distribución de las especies estudiadas. El modelo obtenido discrimina claramente entre áreas favorables y desfavorables con mucha precisión. Se utilizó el modelo para construir un mapa de riesgo de invasión de macrófitos acuáticos para la Península Ibérica que incluyó los resultados de 20 modelos individuales y que muestra que las áreas más vulnerables son las zonas cercanas al mar, las cuencas de los grandes ríos y las zonas con una alta densidad de población. Estos resultados vinculan la importancia del impacto humano en la colonización y la distribución de los macrófitos acuáticos exóticos en la Península Ibérica y, más concretamente, con la Revolución Verde de finales de la década de los setenta. Nuestro trabajo enfatiza la utilidad de los modelos de distribución de especies para la prevención y gestión de invasiones biológicas

Black list and Alert list of the Aquatic Invasive Alien Species in the Iberian Peninsula: an action of the LIFE INVASAQUA

Resumen del trabajo presentado en VI Congreso Nacional sobre Especies Exóticas Invasoras y I Congreso Ibérico sobre EEI (EEI 2022) celebrado en Navarra del 20 al 23 de abril de 2022.One of the objectives of LIFE INVASQUA project is to develop tools that will be more efficient the Early Warning and Rapid Response (EWRR) framework for Invasive Alien Species in the Iberian Peninsula. Horizon scanning for high-risk IAS is basic in implementing measures to reduce new invasions, developing Alert lists, and to focus effort in the species already established, for instance making a Black list. We developed a trans national horizon scanning exercise focused on inland waters of Spain and Portugal in order to provide a prioritized lists (Black list and Alert list) of aquatic IAS that may pose a threat to aquatic ecosystems and socio economic sectors in the future. We followed a step approach of existing information about IAS (Plants, Freshwater Invertebrates, Estuarine Invertebrates and Vertebrates; 127 established taxa in Black list; 90 non established taxa in Alert list) combining with an expert scoring of prioritized taxa. IAS established in the Iberian aquatic system consistently highlighted as the worst included vertebrates (e.g. Cyprinus carpio, Gambusia holbrooki, Silurus glanis), freshwater and estuarine invertebrates (e.g. Procambarus clarkii, Dreissena polymorpha, Pacifastacus leniusculus, Ficopomatus enigmaticus, Callinectes sapidus, Corbicula fluminea) and plants (e.g. Eichhornia crassipes, Azolla filiculoides, Ludwigia grandiflora). Amongst taxa not yet established (Alert list), expert pointed to Perna viridis, Hydroides dirampha, Dreissena bugensis, Procambarus fallax f. virginallis, Perccottus glenii with higher risk of invasion, ecological and socioeconomic impacts. Over 20.6% of the taxa in the preliminary black list received no votes (no prioritization) by experts, 17.8% in the innitial alert list. Our horizon scanning approach is inclusive of all-taxa, prioritizes both established and emerging biological threats across trans-national scales, and considers not only the ecological impact, but also potential direct economic consequences as well as the manageability of invasive species.This work received funds from the LIFE Programme (LIFE17 GIE/ES/000515)

Corrigendum to ‘a horizon scan exercise for aquatic invasive alien species in Iberian inland waters’

info:eu-repo/semantics/publishedVersio

Combining multicriteria decision analysis and GIS to assess vulnerability within a protected area: An objective methodology for managing complex and fragile systems

Characterizing zone fragility is a significant challenge when managing natural areas, but it must be prioritized in conservation efforts. The most commonly employed methodology is to rely on criteria established by experts, which can introduce subjectivity. However, more objective approaches should be used when developing conservation plans. This study follows one methodology focusing on classifying zone vulnerability within a protected natural area, taking as a study case a temporal pond network located in SW Spain; threatened aquatic plants were used as a bioindicators. Spatial data were analyzed using geographic information systems (GIS), and potentially vulnerable zones were identified using multicriteria decision analysis (MCDA) and, more specifically, the weighted overlay method. Criteria weights were determined by variables contribution obtained through species distribution models (SDM), via the maximum entropy algorithm (MaxEnt). The purpose was to avoid artificial bias in decision-making. The analysis indicated that 42.04% of the study area was highly vulnerable. In contrast, only the 14.34% of the study area was at very low risk, meaning it can help maintain pond network biodiversity. These results indicate that potentially vulnerable and crucial zones can be identified using GIS, facilitating the establishment of conservation priorities in a complex system. This methodology could be useful for prioritizing and implementing management and conservation efforts focused on unique species and habitats in protected natural areas

An invasion risk map for non-native aquatic macrophytes of the Iberian Peninsula

Freshwater systems are particularly susceptible to non-native organisms, owing to their high sensitivity to the impacts that are caused by these organisms. Species distribution models, which are based on both environmental and socio-economic variables, facilitate the identification of the most vulnerable areas for the spread of non-native species. We used MaxEnt to predict the potential distribution of 20 non-native aquatic macrophytes in the Iberian Peninsula. Some selected variables, such as the temperature seasonality and the precipitation in the driest quarter, highlight the importance of the climate on their distribution. Notably, the human influence in the territory appears as a key variable in the distribution of studied species. The model discriminated between favorable and unfavorable areas with high accuracy. We used the model to build an invasion risk map of aquatic macrophytes for the Iberian Peninsula that included results from 20 individual models. It showed that the most vulnerable areas are located near to the sea, the major rivers basins, and the high population density areas. These facts suggest the importance of the human impact on the colonization and distribution of non-native aquatic macrophytes in the Iberian Peninsula, and more precisely agricultural development during the Green Revolution at the end of the 70's. Our work also emphasizes the utility of species distribution models for the prevention and management of biological invasions.Peer reviewe

An invasion risk map for non-native aquatic macrophytes of the Iberian Peninsula

Freshwater systems are particularly susceptible to non-native organisms, owing to their high sensitivity to the impacts that are caused by these organisms. Species distribution models, which are based on both environmental and socio-economic variables, facilitate the identification of the most vulnerable areas for the spread of non-native species. We used MaxEnt to predict the potential distribution of 20 non-native aquatic macrophytes in the Iberian Peninsula. Some selected variables, such as the temperature seasonality and the precipitation in the driest quarter, highlight the importance of the climate on their distribution. Notably, the human influence in the territory appears as a key variable in the distribution of studied species. The model discriminated between favorable and unfavorable areas with high accuracy. We used the model to build an invasion risk map of aquatic macrophytes for the Iberian Peninsula that included results from 20 individual models. It showed that the most vulnerable areas are located near to the sea, the major rivers basins, and the high population density areas. These facts suggest the importance of the human impact on the colonization and distribution of non-native aquatic macrophytes in the Iberian Peninsula, and more precisely agricultural development during the Green Revolution at the end of the 70’s. Our work also emphasizes the utility of species distribution models for the prevention and management of biological invasions.Los sistemas acuáticos son especialmente susceptibles a los organismos exóticos debido a su elevada fragilidad y a los impactos que provocan estas especies en este tipo de hábitats. Los modelos de distribución de especies, basados en variables ambientales y socioeconómicas, facilitan la identificación de las áreas más vulnerables ante la expansión de especies exóticas. Se utilizó MaxEnt para predecir la distribución potencial de 20 macrofitos exóticos en la Península Ibérica. Algunas de las variables estudiadas, como la estacionalidad de la temperatura y la precipitación del cuatrimestre más seco, ponen en evidencia la importancia de los factores climáticos en su distribución. Además, la influencia humana en el territorio se presenta como una variable clave en la distribución de las especies estudiadas. El modelo obtenido discrimina claramente entre áreas favorables y desfavorables con mucha precisión. Se utilizó el modelo para construir un mapa de riesgo de invasión de macrófitos acuáticos para la Península Ibérica que incluyó los resultados de 20 modelos individuales y que muestra que las áreas más vulnerables son las zonas cercanas al mar, las cuencas de los grandes ríos y las zonas con una alta densidad de población. Estos resultados vinculan la importancia del impacto humano en la colonización y la distribución de los macrófitos acuáticos exóticos en la Península Ibérica y, más concretamente, con la Revolución Verde de finales de la década de los setenta. Nuestro trabajo enfatiza la utilidad de los modelos de distribución de especies para la prevención y gestión de invasiones biológicas

Combining multicriteria decision analysis and GIS to assess vulnerability within a protected area: An objective methodology for managing complex and fragile systems

Characterizing zone fragility is a significant challenge when managing natural areas, but it must be prioritized in conservation efforts. The most commonly employed methodology is to rely on criteria established by experts, which can introduce subjectivity. However, more objective approaches should be used when developing conservation plans. This study follows one methodology focusing on classifying zone vulnerability within a protected natural area, taking as a study case a temporal pond network located in SW Spain; threatened aquatic plants were used as a bioindicators. Spatial data were analyzed using geographic information systems (GIS), and potentially vulnerable zones were identified using multicriteria decision analysis (MCDA) and, more specifically, the weighted overlay method. Criteria weights were determined by variables contribution obtained through species distribution models (SDM), via the maximum entropy algorithm (MaxEnt). The purpose was to avoid artificial bias in decision-making. The analysis indicated that 42.04% of the study area was highly vulnerable. In contrast, only the 14.34% of the study area was at very low risk, meaning it can help maintain pond network biodiversity. These results indicate that potentially vulnerable and crucial zones can be identified using GIS, facilitating the establishment of conservation priorities in a complex system. This methodology could be useful for prioritizing and implementing management and conservation efforts focused on unique species and habitats in protected natural areas.Ministerio de Agricultura, Alimentación y Medio Ambiente 158/2010CSIC ICTS-RB

Climatic niche shift during Azolla filiculoides invasion and its potential distribution under future scenarios

© The Author(s).In order to prevent future biological invasions, it is crucial to know non-native species distributions. We evaluated the potential global distribution of Azolla filiculoides, a free-floating macrophyte native to the Americas by using species distribution models and niche equivalency tests to analyze the degree of niche overlap between the native and invaded ranges of the species. The models were projected under two future emission scenarios, three global circulation models and two time periods. Our results indicate a possible niche shift between the distribution ranges of the species, indicating that A. filiculoides can adapt to novel environmental conditions derived from climatic differences during the invasion process. Our models also show that the future potential distribution of A. filiculoides will decrease globally, although the species could colonize new vulnerable regions where it is currently absent. We highlight that species occurrence records in the invaded area are necessary to generate accurate models, which will, in turn, improve our ability to predict potential invasion risk areas.Peer reviewe

Climatic Niche Shift during Azolla filiculoides Invasion and Its Potential Distribution under Future Scenarios

In order to prevent future biological invasions, it is crucial to know non-native species distributions. We evaluated the potential global distribution of Azolla filiculoides, a free-floating macrophyte native to the Americas by using species distribution models and niche equivalency tests to analyze the degree of niche overlap between the native and invaded ranges of the species. The models were projected under two future emission scenarios, three global circulation models and two time periods. Our results indicate a possible niche shift between the distribution ranges of the species, indicating that A. filiculoides can adapt to novel environmental conditions derived from climatic differences during the invasion process. Our models also show that the future potential distribution of A. filiculoides will decrease globally, although the species could colonize new vulnerable regions where it is currently absent. We highlight that species occurrence records in the invaded area are necessary to generate accurate models, which will, in turn, improve our ability to predict potential invasion risk areas